MODEL.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "niti = pd.read_csv('NITIDATA.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Capital_Receipts</th>\n",
       "      <th>Aggregate_Receipts</th>\n",
       "      <th>Social_Sector_Expenditure</th>\n",
       "      <th>Interest_Payments</th>\n",
       "      <th>Own_Tax_Revenues</th>\n",
       "      <th>Fiscal_Deficits</th>\n",
       "      <th>Outstanding_Liabilities</th>\n",
       "      <th>Aggregate_Expenditure</th>\n",
       "      <th>Revenue_Receipts</th>\n",
       "      <th>Revenue_Expenditure</th>\n",
       "      <th>Revenue_Deficits</th>\n",
       "      <th>Capital_Expenditure</th>\n",
       "      <th>Nominal_GSDP_Series</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>325.0</td>\n",
       "      <td>1590.0</td>\n",
       "      <td>532.0</td>\n",
       "      <td>81.7</td>\n",
       "      <td>582.0</td>\n",
       "      <td>222.1</td>\n",
       "      <td>81.50</td>\n",
       "      <td>1610.0</td>\n",
       "      <td>1265.0</td>\n",
       "      <td>1161.0</td>\n",
       "      <td>-104.0</td>\n",
       "      <td>449.0</td>\n",
       "      <td>8191.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>187.0</td>\n",
       "      <td>709.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>-27.4</td>\n",
       "      <td>43.41</td>\n",
       "      <td>758.0</td>\n",
       "      <td>522.0</td>\n",
       "      <td>357.0</td>\n",
       "      <td>-165.0</td>\n",
       "      <td>401.0</td>\n",
       "      <td>2516.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>702.0</td>\n",
       "      <td>1690.0</td>\n",
       "      <td>452.0</td>\n",
       "      <td>107.1</td>\n",
       "      <td>277.0</td>\n",
       "      <td>335.8</td>\n",
       "      <td>106.33</td>\n",
       "      <td>1791.0</td>\n",
       "      <td>988.0</td>\n",
       "      <td>929.0</td>\n",
       "      <td>-59.0</td>\n",
       "      <td>862.0</td>\n",
       "      <td>7353.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>345.0</td>\n",
       "      <td>1370.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>68.6</td>\n",
       "      <td>531.0</td>\n",
       "      <td>246.5</td>\n",
       "      <td>80.76</td>\n",
       "      <td>1442.0</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>903.0</td>\n",
       "      <td>-122.0</td>\n",
       "      <td>539.0</td>\n",
       "      <td>7427.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>116.0</td>\n",
       "      <td>576.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>234.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>30.76</td>\n",
       "      <td>607.0</td>\n",
       "      <td>460.0</td>\n",
       "      <td>401.0</td>\n",
       "      <td>-59.0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>3386.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Capital_Receipts  Aggregate_Receipts  Social_Sector_Expenditure  \\\n",
       "0             325.0              1590.0                      532.0   \n",
       "1             187.0               709.0                      171.0   \n",
       "2             702.0              1690.0                      452.0   \n",
       "3             345.0              1370.0                      406.0   \n",
       "4             116.0               576.0                      137.0   \n",
       "\n",
       "   Interest_Payments  Own_Tax_Revenues  Fiscal_Deficits  \\\n",
       "0               81.7             582.0            222.1   \n",
       "1               30.0              66.0            -27.4   \n",
       "2              107.1             277.0            335.8   \n",
       "3               68.6             531.0            246.5   \n",
       "4               37.0             234.0            112.0   \n",
       "\n",
       "   Outstanding_Liabilities  Aggregate_Expenditure  Revenue_Receipts  \\\n",
       "0                    81.50                 1610.0            1265.0   \n",
       "1                    43.41                  758.0             522.0   \n",
       "2                   106.33                 1791.0             988.0   \n",
       "3                    80.76                 1442.0            1025.0   \n",
       "4                    30.76                  607.0             460.0   \n",
       "\n",
       "   Revenue_Expenditure  Revenue_Deficits  Capital_Expenditure  \\\n",
       "0               1161.0            -104.0                449.0   \n",
       "1                357.0            -165.0                401.0   \n",
       "2                929.0             -59.0                862.0   \n",
       "3                903.0            -122.0                539.0   \n",
       "4                401.0             -59.0                207.0   \n",
       "\n",
       "   Nominal_GSDP_Series  \n",
       "0               8191.0  \n",
       "1               2516.0  \n",
       "2               7353.0  \n",
       "3               7427.0  \n",
       "4               3386.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "niti.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Capital_Receipts</th>\n",
       "      <td>660.0</td>\n",
       "      <td>2428.893939</td>\n",
       "      <td>4110.573309</td>\n",
       "      <td>-5116.00</td>\n",
       "      <td>238.7500</td>\n",
       "      <td>811.50</td>\n",
       "      <td>2583.750</td>\n",
       "      <td>37639.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aggregate_Receipts</th>\n",
       "      <td>660.0</td>\n",
       "      <td>7791.672727</td>\n",
       "      <td>10883.932609</td>\n",
       "      <td>38.00</td>\n",
       "      <td>1143.5000</td>\n",
       "      <td>3191.50</td>\n",
       "      <td>9882.000</td>\n",
       "      <td>72074.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Social_Sector_Expenditure</th>\n",
       "      <td>660.0</td>\n",
       "      <td>2623.565152</td>\n",
       "      <td>3470.775608</td>\n",
       "      <td>9.00</td>\n",
       "      <td>381.2500</td>\n",
       "      <td>1114.00</td>\n",
       "      <td>3512.000</td>\n",
       "      <td>24268.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Interest_Payments</th>\n",
       "      <td>660.0</td>\n",
       "      <td>1060.228030</td>\n",
       "      <td>1757.027349</td>\n",
       "      <td>0.00</td>\n",
       "      <td>81.7000</td>\n",
       "      <td>290.00</td>\n",
       "      <td>1240.000</td>\n",
       "      <td>11870.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Own_Tax_Revenues</th>\n",
       "      <td>660.0</td>\n",
       "      <td>2604.877273</td>\n",
       "      <td>4224.076558</td>\n",
       "      <td>0.00</td>\n",
       "      <td>90.0000</td>\n",
       "      <td>879.50</td>\n",
       "      <td>3174.750</td>\n",
       "      <td>33540.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fiscal_Deficits</th>\n",
       "      <td>660.0</td>\n",
       "      <td>1630.949848</td>\n",
       "      <td>2688.436374</td>\n",
       "      <td>-360.00</td>\n",
       "      <td>159.9500</td>\n",
       "      <td>517.00</td>\n",
       "      <td>1736.150</td>\n",
       "      <td>18620.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Outstanding_Liabilities</th>\n",
       "      <td>660.0</td>\n",
       "      <td>417.522303</td>\n",
       "      <td>596.079415</td>\n",
       "      <td>1.42</td>\n",
       "      <td>49.6725</td>\n",
       "      <td>177.21</td>\n",
       "      <td>505.725</td>\n",
       "      <td>4067.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aggregate_Expenditure</th>\n",
       "      <td>660.0</td>\n",
       "      <td>7663.422727</td>\n",
       "      <td>10658.752422</td>\n",
       "      <td>43.00</td>\n",
       "      <td>1175.5000</td>\n",
       "      <td>3078.50</td>\n",
       "      <td>9737.250</td>\n",
       "      <td>72668.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Revenue_Receipts</th>\n",
       "      <td>660.0</td>\n",
       "      <td>5362.778788</td>\n",
       "      <td>7044.667651</td>\n",
       "      <td>37.00</td>\n",
       "      <td>892.5000</td>\n",
       "      <td>2347.50</td>\n",
       "      <td>7210.750</td>\n",
       "      <td>48438.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Revenue_Expenditure</th>\n",
       "      <td>660.0</td>\n",
       "      <td>6022.030303</td>\n",
       "      <td>8317.578141</td>\n",
       "      <td>30.00</td>\n",
       "      <td>864.0000</td>\n",
       "      <td>2275.50</td>\n",
       "      <td>7755.000</td>\n",
       "      <td>52280.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Revenue_Deficits</th>\n",
       "      <td>660.0</td>\n",
       "      <td>659.255455</td>\n",
       "      <td>1824.575250</td>\n",
       "      <td>-4328.00</td>\n",
       "      <td>-62.3750</td>\n",
       "      <td>41.25</td>\n",
       "      <td>594.675</td>\n",
       "      <td>18583.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Capital_Expenditure</th>\n",
       "      <td>660.0</td>\n",
       "      <td>1641.445455</td>\n",
       "      <td>2554.712652</td>\n",
       "      <td>13.00</td>\n",
       "      <td>289.5000</td>\n",
       "      <td>797.00</td>\n",
       "      <td>1851.750</td>\n",
       "      <td>21622.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nominal_GSDP_Series</th>\n",
       "      <td>660.0</td>\n",
       "      <td>37596.312121</td>\n",
       "      <td>57944.592770</td>\n",
       "      <td>52.00</td>\n",
       "      <td>2963.0000</td>\n",
       "      <td>14311.00</td>\n",
       "      <td>44635.000</td>\n",
       "      <td>486766.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                           count          mean           std      min  \\\n",
       "Capital_Receipts           660.0   2428.893939   4110.573309 -5116.00   \n",
       "Aggregate_Receipts         660.0   7791.672727  10883.932609    38.00   \n",
       "Social_Sector_Expenditure  660.0   2623.565152   3470.775608     9.00   \n",
       "Interest_Payments          660.0   1060.228030   1757.027349     0.00   \n",
       "Own_Tax_Revenues           660.0   2604.877273   4224.076558     0.00   \n",
       "Fiscal_Deficits            660.0   1630.949848   2688.436374  -360.00   \n",
       "Outstanding_Liabilities    660.0    417.522303    596.079415     1.42   \n",
       "Aggregate_Expenditure      660.0   7663.422727  10658.752422    43.00   \n",
       "Revenue_Receipts           660.0   5362.778788   7044.667651    37.00   \n",
       "Revenue_Expenditure        660.0   6022.030303   8317.578141    30.00   \n",
       "Revenue_Deficits           660.0    659.255455   1824.575250 -4328.00   \n",
       "Capital_Expenditure        660.0   1641.445455   2554.712652    13.00   \n",
       "Nominal_GSDP_Series        660.0  37596.312121  57944.592770    52.00   \n",
       "\n",
       "                                 25%       50%        75%       max  \n",
       "Capital_Receipts            238.7500    811.50   2583.750   37639.0  \n",
       "Aggregate_Receipts         1143.5000   3191.50   9882.000   72074.0  \n",
       "Social_Sector_Expenditure   381.2500   1114.00   3512.000   24268.0  \n",
       "Interest_Payments            81.7000    290.00   1240.000   11870.0  \n",
       "Own_Tax_Revenues             90.0000    879.50   3174.750   33540.0  \n",
       "Fiscal_Deficits             159.9500    517.00   1736.150   18620.0  \n",
       "Outstanding_Liabilities      49.6725    177.21    505.725    4067.4  \n",
       "Aggregate_Expenditure      1175.5000   3078.50   9737.250   72668.0  \n",
       "Revenue_Receipts            892.5000   2347.50   7210.750   48438.0  \n",
       "Revenue_Expenditure         864.0000   2275.50   7755.000   52280.0  \n",
       "Revenue_Deficits            -62.3750     41.25    594.675   18583.0  \n",
       "Capital_Expenditure         289.5000    797.00   1851.750   21622.0  \n",
       "Nominal_GSDP_Series        2963.0000  14311.00  44635.000  486766.0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "niti.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Capital_Receipts</th>\n",
       "      <th>Aggregate_Receipts</th>\n",
       "      <th>Social_Sector_Expenditure</th>\n",
       "      <th>Interest_Payments</th>\n",
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       "      <th>Aggregate_Expenditure</th>\n",
       "      <th>Revenue_Receipts</th>\n",
       "      <th>Revenue_Expenditure</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Capital_Receipts</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.958102</td>\n",
       "      <td>0.901525</td>\n",
       "      <td>0.945287</td>\n",
       "      <td>0.864848</td>\n",
       "      <td>0.939052</td>\n",
       "      <td>0.914235</td>\n",
       "      <td>0.952641</td>\n",
       "      <td>0.896756</td>\n",
       "      <td>0.931491</td>\n",
       "      <td>0.783977</td>\n",
       "      <td>0.941874</td>\n",
       "      <td>0.904869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aggregate_Receipts</th>\n",
       "      <td>0.958102</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.976070</td>\n",
       "      <td>0.955550</td>\n",
       "      <td>0.946278</td>\n",
       "      <td>0.922980</td>\n",
       "      <td>0.956505</td>\n",
       "      <td>0.996875</td>\n",
       "      <td>0.985935</td>\n",
       "      <td>0.989615</td>\n",
       "      <td>0.704623</td>\n",
       "      <td>0.937185</td>\n",
       "      <td>0.956340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Social_Sector_Expenditure</th>\n",
       "      <td>0.901525</td>\n",
       "      <td>0.976070</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.923355</td>\n",
       "      <td>0.945140</td>\n",
       "      <td>0.916260</td>\n",
       "      <td>0.948411</td>\n",
       "      <td>0.978583</td>\n",
       "      <td>0.981976</td>\n",
       "      <td>0.983376</td>\n",
       "      <td>0.691462</td>\n",
       "      <td>0.881187</td>\n",
       "      <td>0.951463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Interest_Payments</th>\n",
       "      <td>0.945287</td>\n",
       "      <td>0.955550</td>\n",
       "      <td>0.923355</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.856082</td>\n",
       "      <td>0.935745</td>\n",
       "      <td>0.953921</td>\n",
       "      <td>0.958109</td>\n",
       "      <td>0.924738</td>\n",
       "      <td>0.955489</td>\n",
       "      <td>0.785332</td>\n",
       "      <td>0.886556</td>\n",
       "      <td>0.909927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Own_Tax_Revenues</th>\n",
       "      <td>0.864848</td>\n",
       "      <td>0.946278</td>\n",
       "      <td>0.945140</td>\n",
       "      <td>0.856082</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.847567</td>\n",
       "      <td>0.903109</td>\n",
       "      <td>0.942623</td>\n",
       "      <td>0.957349</td>\n",
       "      <td>0.942143</td>\n",
       "      <td>0.598584</td>\n",
       "      <td>0.865397</td>\n",
       "      <td>0.957997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fiscal_Deficits</th>\n",
       "      <td>0.939052</td>\n",
       "      <td>0.922980</td>\n",
       "      <td>0.916260</td>\n",
       "      <td>0.935745</td>\n",
       "      <td>0.847567</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.927833</td>\n",
       "      <td>0.936765</td>\n",
       "      <td>0.878056</td>\n",
       "      <td>0.935389</td>\n",
       "      <td>0.873941</td>\n",
       "      <td>0.862949</td>\n",
       "      <td>0.904112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Outstanding_Liabilities</th>\n",
       "      <td>0.914235</td>\n",
       "      <td>0.956505</td>\n",
       "      <td>0.948411</td>\n",
       "      <td>0.953921</td>\n",
       "      <td>0.903109</td>\n",
       "      <td>0.927833</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.957928</td>\n",
       "      <td>0.944332</td>\n",
       "      <td>0.964662</td>\n",
       "      <td>0.751491</td>\n",
       "      <td>0.855936</td>\n",
       "      <td>0.954329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aggregate_Expenditure</th>\n",
       "      <td>0.952641</td>\n",
       "      <td>0.996875</td>\n",
       "      <td>0.978583</td>\n",
       "      <td>0.958109</td>\n",
       "      <td>0.942623</td>\n",
       "      <td>0.936765</td>\n",
       "      <td>0.957928</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.984293</td>\n",
       "      <td>0.994104</td>\n",
       "      <td>0.731423</td>\n",
       "      <td>0.935613</td>\n",
       "      <td>0.953906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Revenue_Receipts</th>\n",
       "      <td>0.896756</td>\n",
       "      <td>0.985935</td>\n",
       "      <td>0.981976</td>\n",
       "      <td>0.924738</td>\n",
       "      <td>0.957349</td>\n",
       "      <td>0.878056</td>\n",
       "      <td>0.944332</td>\n",
       "      <td>0.984293</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.985418</td>\n",
       "      <td>0.631183</td>\n",
       "      <td>0.898356</td>\n",
       "      <td>0.949542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Revenue_Expenditure</th>\n",
       "      <td>0.931491</td>\n",
       "      <td>0.989615</td>\n",
       "      <td>0.983376</td>\n",
       "      <td>0.955489</td>\n",
       "      <td>0.942143</td>\n",
       "      <td>0.935389</td>\n",
       "      <td>0.964662</td>\n",
       "      <td>0.994104</td>\n",
       "      <td>0.985418</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.753954</td>\n",
       "      <td>0.891816</td>\n",
       "      <td>0.953390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Revenue_Deficits</th>\n",
       "      <td>0.783977</td>\n",
       "      <td>0.704623</td>\n",
       "      <td>0.691462</td>\n",
       "      <td>0.785332</td>\n",
       "      <td>0.598584</td>\n",
       "      <td>0.873941</td>\n",
       "      <td>0.751491</td>\n",
       "      <td>0.731423</td>\n",
       "      <td>0.631183</td>\n",
       "      <td>0.753954</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.596941</td>\n",
       "      <td>0.679997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Capital_Expenditure</th>\n",
       "      <td>0.941874</td>\n",
       "      <td>0.937185</td>\n",
       "      <td>0.881187</td>\n",
       "      <td>0.886556</td>\n",
       "      <td>0.865397</td>\n",
       "      <td>0.862949</td>\n",
       "      <td>0.855936</td>\n",
       "      <td>0.935613</td>\n",
       "      <td>0.898356</td>\n",
       "      <td>0.891816</td>\n",
       "      <td>0.596941</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.875852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nominal_GSDP_Series</th>\n",
       "      <td>0.904869</td>\n",
       "      <td>0.956340</td>\n",
       "      <td>0.951463</td>\n",
       "      <td>0.909927</td>\n",
       "      <td>0.957997</td>\n",
       "      <td>0.904112</td>\n",
       "      <td>0.954329</td>\n",
       "      <td>0.953906</td>\n",
       "      <td>0.949542</td>\n",
       "      <td>0.953390</td>\n",
       "      <td>0.679997</td>\n",
       "      <td>0.875852</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Capital_Receipts  Aggregate_Receipts  \\\n",
       "Capital_Receipts                   1.000000            0.958102   \n",
       "Aggregate_Receipts                 0.958102            1.000000   \n",
       "Social_Sector_Expenditure          0.901525            0.976070   \n",
       "Interest_Payments                  0.945287            0.955550   \n",
       "Own_Tax_Revenues                   0.864848            0.946278   \n",
       "Fiscal_Deficits                    0.939052            0.922980   \n",
       "Outstanding_Liabilities            0.914235            0.956505   \n",
       "Aggregate_Expenditure              0.952641            0.996875   \n",
       "Revenue_Receipts                   0.896756            0.985935   \n",
       "Revenue_Expenditure                0.931491            0.989615   \n",
       "Revenue_Deficits                   0.783977            0.704623   \n",
       "Capital_Expenditure                0.941874            0.937185   \n",
       "Nominal_GSDP_Series                0.904869            0.956340   \n",
       "\n",
       "                           Social_Sector_Expenditure  Interest_Payments  \\\n",
       "Capital_Receipts                            0.901525           0.945287   \n",
       "Aggregate_Receipts                          0.976070           0.955550   \n",
       "Social_Sector_Expenditure                   1.000000           0.923355   \n",
       "Interest_Payments                           0.923355           1.000000   \n",
       "Own_Tax_Revenues                            0.945140           0.856082   \n",
       "Fiscal_Deficits                             0.916260           0.935745   \n",
       "Outstanding_Liabilities                     0.948411           0.953921   \n",
       "Aggregate_Expenditure                       0.978583           0.958109   \n",
       "Revenue_Receipts                            0.981976           0.924738   \n",
       "Revenue_Expenditure                         0.983376           0.955489   \n",
       "Revenue_Deficits                            0.691462           0.785332   \n",
       "Capital_Expenditure                         0.881187           0.886556   \n",
       "Nominal_GSDP_Series                         0.951463           0.909927   \n",
       "\n",
       "                           Own_Tax_Revenues  Fiscal_Deficits  \\\n",
       "Capital_Receipts                   0.864848         0.939052   \n",
       "Aggregate_Receipts                 0.946278         0.922980   \n",
       "Social_Sector_Expenditure          0.945140         0.916260   \n",
       "Interest_Payments                  0.856082         0.935745   \n",
       "Own_Tax_Revenues                   1.000000         0.847567   \n",
       "Fiscal_Deficits                    0.847567         1.000000   \n",
       "Outstanding_Liabilities            0.903109         0.927833   \n",
       "Aggregate_Expenditure              0.942623         0.936765   \n",
       "Revenue_Receipts                   0.957349         0.878056   \n",
       "Revenue_Expenditure                0.942143         0.935389   \n",
       "Revenue_Deficits                   0.598584         0.873941   \n",
       "Capital_Expenditure                0.865397         0.862949   \n",
       "Nominal_GSDP_Series                0.957997         0.904112   \n",
       "\n",
       "                           Outstanding_Liabilities  Aggregate_Expenditure  \\\n",
       "Capital_Receipts                          0.914235               0.952641   \n",
       "Aggregate_Receipts                        0.956505               0.996875   \n",
       "Social_Sector_Expenditure                 0.948411               0.978583   \n",
       "Interest_Payments                         0.953921               0.958109   \n",
       "Own_Tax_Revenues                          0.903109               0.942623   \n",
       "Fiscal_Deficits                           0.927833               0.936765   \n",
       "Outstanding_Liabilities                   1.000000               0.957928   \n",
       "Aggregate_Expenditure                     0.957928               1.000000   \n",
       "Revenue_Receipts                          0.944332               0.984293   \n",
       "Revenue_Expenditure                       0.964662               0.994104   \n",
       "Revenue_Deficits                          0.751491               0.731423   \n",
       "Capital_Expenditure                       0.855936               0.935613   \n",
       "Nominal_GSDP_Series                       0.954329               0.953906   \n",
       "\n",
       "                           Revenue_Receipts  Revenue_Expenditure  \\\n",
       "Capital_Receipts                   0.896756             0.931491   \n",
       "Aggregate_Receipts                 0.985935             0.989615   \n",
       "Social_Sector_Expenditure          0.981976             0.983376   \n",
       "Interest_Payments                  0.924738             0.955489   \n",
       "Own_Tax_Revenues                   0.957349             0.942143   \n",
       "Fiscal_Deficits                    0.878056             0.935389   \n",
       "Outstanding_Liabilities            0.944332             0.964662   \n",
       "Aggregate_Expenditure              0.984293             0.994104   \n",
       "Revenue_Receipts                   1.000000             0.985418   \n",
       "Revenue_Expenditure                0.985418             1.000000   \n",
       "Revenue_Deficits                   0.631183             0.753954   \n",
       "Capital_Expenditure                0.898356             0.891816   \n",
       "Nominal_GSDP_Series                0.949542             0.953390   \n",
       "\n",
       "                           Revenue_Deficits  Capital_Expenditure  \\\n",
       "Capital_Receipts                   0.783977             0.941874   \n",
       "Aggregate_Receipts                 0.704623             0.937185   \n",
       "Social_Sector_Expenditure          0.691462             0.881187   \n",
       "Interest_Payments                  0.785332             0.886556   \n",
       "Own_Tax_Revenues                   0.598584             0.865397   \n",
       "Fiscal_Deficits                    0.873941             0.862949   \n",
       "Outstanding_Liabilities            0.751491             0.855936   \n",
       "Aggregate_Expenditure              0.731423             0.935613   \n",
       "Revenue_Receipts                   0.631183             0.898356   \n",
       "Revenue_Expenditure                0.753954             0.891816   \n",
       "Revenue_Deficits                   1.000000             0.596941   \n",
       "Capital_Expenditure                0.596941             1.000000   \n",
       "Nominal_GSDP_Series                0.679997             0.875852   \n",
       "\n",
       "                           Nominal_GSDP_Series  \n",
       "Capital_Receipts                      0.904869  \n",
       "Aggregate_Receipts                    0.956340  \n",
       "Social_Sector_Expenditure             0.951463  \n",
       "Interest_Payments                     0.909927  \n",
       "Own_Tax_Revenues                      0.957997  \n",
       "Fiscal_Deficits                       0.904112  \n",
       "Outstanding_Liabilities               0.954329  \n",
       "Aggregate_Expenditure                 0.953906  \n",
       "Revenue_Receipts                      0.949542  \n",
       "Revenue_Expenditure                   0.953390  \n",
       "Revenue_Deficits                      0.679997  \n",
       "Capital_Expenditure                   0.875852  \n",
       "Nominal_GSDP_Series                   1.000000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "niti.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Split the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = niti.iloc[:, 0:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(660, 12)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Capital_Receipts</th>\n",
       "      <th>Aggregate_Receipts</th>\n",
       "      <th>Social_Sector_Expenditure</th>\n",
       "      <th>Interest_Payments</th>\n",
       "      <th>Own_Tax_Revenues</th>\n",
       "      <th>Fiscal_Deficits</th>\n",
       "      <th>Outstanding_Liabilities</th>\n",
       "      <th>Aggregate_Expenditure</th>\n",
       "      <th>Revenue_Receipts</th>\n",
       "      <th>Revenue_Expenditure</th>\n",
       "      <th>Revenue_Deficits</th>\n",
       "      <th>Capital_Expenditure</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>325.0</td>\n",
       "      <td>1590.0</td>\n",
       "      <td>532.0</td>\n",
       "      <td>81.7</td>\n",
       "      <td>582.0</td>\n",
       "      <td>222.1</td>\n",
       "      <td>81.50</td>\n",
       "      <td>1610.0</td>\n",
       "      <td>1265.0</td>\n",
       "      <td>1161.0</td>\n",
       "      <td>-104.0</td>\n",
       "      <td>449.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>187.0</td>\n",
       "      <td>709.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>-27.4</td>\n",
       "      <td>43.41</td>\n",
       "      <td>758.0</td>\n",
       "      <td>522.0</td>\n",
       "      <td>357.0</td>\n",
       "      <td>-165.0</td>\n",
       "      <td>401.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>702.0</td>\n",
       "      <td>1690.0</td>\n",
       "      <td>452.0</td>\n",
       "      <td>107.1</td>\n",
       "      <td>277.0</td>\n",
       "      <td>335.8</td>\n",
       "      <td>106.33</td>\n",
       "      <td>1791.0</td>\n",
       "      <td>988.0</td>\n",
       "      <td>929.0</td>\n",
       "      <td>-59.0</td>\n",
       "      <td>862.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>345.0</td>\n",
       "      <td>1370.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>68.6</td>\n",
       "      <td>531.0</td>\n",
       "      <td>246.5</td>\n",
       "      <td>80.76</td>\n",
       "      <td>1442.0</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>903.0</td>\n",
       "      <td>-122.0</td>\n",
       "      <td>539.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>116.0</td>\n",
       "      <td>576.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>234.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>30.76</td>\n",
       "      <td>607.0</td>\n",
       "      <td>460.0</td>\n",
       "      <td>401.0</td>\n",
       "      <td>-59.0</td>\n",
       "      <td>207.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Capital_Receipts  Aggregate_Receipts  Social_Sector_Expenditure  \\\n",
       "0             325.0              1590.0                      532.0   \n",
       "1             187.0               709.0                      171.0   \n",
       "2             702.0              1690.0                      452.0   \n",
       "3             345.0              1370.0                      406.0   \n",
       "4             116.0               576.0                      137.0   \n",
       "\n",
       "   Interest_Payments  Own_Tax_Revenues  Fiscal_Deficits  \\\n",
       "0               81.7             582.0            222.1   \n",
       "1               30.0              66.0            -27.4   \n",
       "2              107.1             277.0            335.8   \n",
       "3               68.6             531.0            246.5   \n",
       "4               37.0             234.0            112.0   \n",
       "\n",
       "   Outstanding_Liabilities  Aggregate_Expenditure  Revenue_Receipts  \\\n",
       "0                    81.50                 1610.0            1265.0   \n",
       "1                    43.41                  758.0             522.0   \n",
       "2                   106.33                 1791.0             988.0   \n",
       "3                    80.76                 1442.0            1025.0   \n",
       "4                    30.76                  607.0             460.0   \n",
       "\n",
       "   Revenue_Expenditure  Revenue_Deficits  Capital_Expenditure  \n",
       "0               1161.0            -104.0                449.0  \n",
       "1                357.0            -165.0                401.0  \n",
       "2                929.0             -59.0                862.0  \n",
       "3                903.0            -122.0                539.0  \n",
       "4                401.0             -59.0                207.0  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y = niti.iloc[:, -1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature Scaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = scaler.fit_transform(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neural_network import MLPRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = MLPRegressor(hidden_layer_sizes=(12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12), max_iter=5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MLPRegressor(activation='relu', alpha=0.0001, batch_size='auto', beta_1=0.9,\n",
       "       beta_2=0.999, early_stopping=False, epsilon=1e-08,\n",
       "       hidden_layer_sizes=(12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12),\n",
       "       learning_rate='constant', learning_rate_init=0.001, max_iter=5000,\n",
       "       momentum=0.9, n_iter_no_change=10, nesterovs_momentum=True,\n",
       "       power_t=0.5, random_state=None, shuffle=True, solver='adam',\n",
       "       tol=0.0001, validation_fraction=0.1, verbose=False,\n",
       "       warm_start=False)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X_train, Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9531020120990584"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.score(X_test, Y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyze the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error, r2_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "Ya = Y_test\n",
    "Yp = model.predict(X_test)\n",
    "mse = mean_squared_error(Ya, Yp)\n",
    "R2 = r2_score(Ya, Yp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'MSE : 160203075.99019524, RMSE : 12657.1353785205, R2-Score : 0.9531020120990584'"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'MSE : {}, RMSE : {}, R2-Score : {}'.format(mse, np.sqrt(mse), R2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save the Model and the Scaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "from sklearn.externals import joblib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = 'gdp_model.sav'\n",
    "scalerfile = 'gdp_scale.sav'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'model' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-4-d1b95c79dc98>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mfilename\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'gdp_model.sav'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mscalerfile\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'gdp_scale.sav'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mpickle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'wb'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[0mpickle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscaler\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscalerfile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'wb'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'model' is not defined"
     ]
    }
   ],
   "source": [
    "pickle.dump(model, open(filename, 'wb'))\n",
    "pickle.dump(scaler, open(scalerfile, 'wb'))\n",
    "\n",
    "# using JobLib\n",
    "joblib.dump(model, 'gdp.model')\n",
    "joblib.dump(scaler, 'gdp.scaler')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the Model and the Scaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'X_test' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-6-789df47c95d3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mloaded_model\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpickle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'rb'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mloaded_scaler\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpickle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscalerfile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'rb'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mloaded_model\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscore\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_test\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mY_test\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'X_test' is not defined"
     ]
    }
   ],
   "source": [
    "loaded_model = pickle.load(open(filename, 'rb'))\n",
    "loaded_scaler = pickle.load(open(scalerfile, 'rb'))\n",
    "result = loaded_model.score(X_test, Y_test)\n",
    "print(result)"
   ]
  }
 ],
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